Getting Prediction On Created And Learned Model.

After the two first steps are done, and you end up with a created, saved and learned model, you can get the forecasting results from your model.

Click the PREDICT button, and in the popup menu, you can select different historical periods which are used for building the forecasting results.

There’re several options under prediction menu-for 15 bars, for 30, 45 and 60. There’s no difference between them, except one-that the forecasting signals are built for the last N days. You may use these options to determine if the model is successfully learned on different periods, and the performance on these periods seems to be similar.

Another forecasting options-predict on entire dataset, and predict on out of sample period-will give you the ability to determine the overall model’s performance on whole period used in modeling (entire dataset), and on out-of-sample period which was not used in learning process, and which is ‘unknown’ for the system just like it is fresh updated data. Looking at entire data set forecasting results, you can see how good is your model, how strong is its memory filled during learning, and if it was successfully learned for recognizing data sets of in-sample period.

Out-of-sample period predictions show you how successfully you selected the model’s parameters, and if it able to work with unknown data and give correct forecasting results. And of course, how successful your model was learned. So, selecting this option will give you forecasting signals for last N days which were reserved as ‘unknown’ by the system, and which can be used for estimating ‘real’ model’s performance and accuracy.

If you selected to use out-of-sample data (backtesting period), there will be an option available to predict using the Out-Of-Sample period. This will give you the ability to generate predictions on the data which was not used in learning, and estimate a model’s quality of generated signals.

The given results appear as BUY/SELL signals for the chosen period. The signals appear on the Chart page. The signal under the last day’s data is the presumed market movement.

RED and GREEN signals are active signals which gives you the recommendation to enter the market or exit. Grayed arrows are inactive signals, generated by neural network, but, they are used for supporting previous active signals. So, when the first GREEN arrow appears at the chart, you get the recommendation to go LONG and to BUY some shares tomorrow at open (you also can see this recommendation at CURRENT POSITION INFO tab). You buy some shares then, update the model, and get new forecasting. But, for new bar appeared after updating, there's BUY signal again, which is supporting signal telling that you're on right side, and, as you're in LONG position already, you do nothing tomorrow at open, and that BUY signal is grayed as inactive. As soon as the first SELL signal appears after several BUY signals, you get active RED arrow, and SELL recommendation at CURRENT POSITION INFO tab. This is your recommendation to close previously opened LONG position, and sell the shares tomorrow at open. After the shares are sold, you wait for the next active signal, red or green, for going SHORT or LONG.

If there’s a SELL signal, it means that the market moves down. If BUY, the market moves up. If there’s no signal, it means that the system gives a HOLD signal. Taking into consideration your model’s training level and out-of-sample testing results, you can make decisions about your further market activity. You also can use embedded technical analysis module for plotting indicators, which may be used for supporting your decision to go with given recommendations.